Director/Senior Director, Molecular Discovery

Lilasciences; Cambridge, San Francisco (MA, CA); On-site; USD 202,000 - 323,000; Full time

Benefits offered by this job

Comprehensive benefits

Parental leave

Educational assistance

Commuter benefits

Lunch program

Job summary

Lila Sciences seeks a Director of Molecular Discovery to lead small-molecule programs from hit to lead and candidate nomination in Cambridge, MA. You will own discovery output, set timelines and quality targets, and liaise with the autonomous platform and decision-makers to ensure potency, selectivity, and developability.

You will work closely with AI/ML, robotics, and software teams to improve platform performance and accelerate delivery of clinical candidates, shaping program architecture,

Qualifications

• Ph.D. in medicinal chemistry, computational chemistry, chemical biology, or a closely related discipline.
• 12+ years of experience in small molecule drug discovery with at least 5 years in a senior role closely involved in advancing compounds from hit-to-lead through candidate selection.
• Demonstrated involvement in programs that delivered clinical candidates with proximity to compound progression decisions.
• Deep fluency in medicinal chemistry principles, including SAR, synthetic tractability, and multi-parameter tradeoffs.
• Operational mindset with experience running discovery programs, clear metrics, milestones, and accountability.
• Strong knowledge of ADMET, DMPK, and data packages required to advance a candidate to IND-enabling studies.
• Fluency with AI/ML-driven molecular design approaches and the ability to collaborate with scientists who build models.
• Effective communicator capable of translating complex status updates for leadership.

Responsibilities

• Own discovery programs from hit identification through lead optimization and candidate nomination.
• Lead timelines, quality benchmarks, and throughput targets across active programs.
• Interface between the autonomous platform and decision-making to ensure potency, selectivity, ADMET, and developability.
• Collaborate with AI/ML, robotics, and software teams to improve platform performance and predictive accuracy.
• Architect discovery programs end-to-end, define assays, sourcing capabilities, and manage scientific staff.
• Facilitate relationships with CROs and external partners for specialized studies (e.g., DMPK, in vivo pharmacology).
• Provide drug discovery expertise to product teams for partnerships with pharma/biotech.

Skills

Medicinal chemistry

Computational chemistry

Chemical biology

Drug discovery leadership

ADMET knowledge

DMPK knowledge

AI/ML design

Program leadership

Communication skills

Education

Ph.D. in medicinal chemistry or related field

Job description

Your Impact at LILA

The Director, Molecular Discovery is responsible for ensuring our autonomous science platform reliably and repeatedly delivers validated small-molecule drug candidates against designated targets at increasing speed. The platform generates and tests hypotheses at superhuman scale, and you ensure that process translates into real, high-quality compounds that advance toward the clinic.

This role leans heavily into the AI and computational side of our workflow: you will be accountable for throughput, quality, and the operational health of the discovery engine, working hand-in-hand with AI scientists, computational chemists, and platform engineers to diagnose bottlenecks, close feedback loops, and continuously improve how the platform performs.

What You'll Be Building

• Own small molecule discovery programs against assigned targets, from hit identification through lead optimization and candidate nomination.
• Serve as the accountable leader for discovery output setting and hitting timelines, quality benchmarks, and throughput targets across active programs.
• Operate as the primary interface between the autonomous science platform and drug discovery decision‑making, ensuring that what the platform produces meets the bar for potency, selectivity, ADMET properties, and developability.
• Collaborate daily with AI/ML, robotics, and software engineering teams to close the loop between computational predictions and experimental results, driving continuous improvement of the platform's predictive accuracy and experimental efficiency.
• Architect the components of each discovery program end to end, specifying the required assays, building or sourcing the right capabilities, and managing the scientific staff needed to execute. Define and enforce the quality standards, assay cascades, and decision criteria that govern how compounds progress through the pipeline.
• Facilitate relationships with CROs and external partners for specialized studies (e.g., in vivo pharmacology, safety pharmacology, DMPK) that sit outside the automated platform.
• Provide drug discovery expertise to Lila's product team for commercial partnerships, translating platform capabilities into credible value propositions for pharma and biotech collaborators.

What You'll Need to Succeed

• Ph.D. in medicinal chemistry, computational chemistry, chemical biology, or a closely related discipline.
• 12+ years of experience in small molecule drug discovery from the computational, medicinal chemistry, or program leadership side with at least 5 years in a senior role closely involved in advancing compounds from hit-to-lead through candidate selection.
• Demonstrated involvement in programs that delivered clinical candidates, with enough proximity to compound progression decisions to own them whether from the computational, medicinal chemistry, or program leadership side.
• Deep fluency in medicinal chemistry principles, you may not have practiced bench medchem, but you understand SAR, synthetic tractability, and the multiparameter tradeoffs at the core of lead optimization (potency, selectivity, ADMET, PK, safety) well enough to guide them or define systematic decision frameworks for them.
• Operational mindset, experience running discovery programs with clear metrics, milestones, and accountability structures, and a comfort level with managing throughput and efficiency alongside scientific quality.
• Strong working knowledge of ADMET, DMPK, and the data packages required to advance a candidate to IND‑enabling studies.
• Fluency with AI/ML‑driven molecular design approaches (generative chemistry, molecular property prediction, free energy methods, active learning) and the practical judgment to know when computational output is actionable and when it needs experimental validation. You don’t need to build models, but you must be a credible, hands‑on collaborator with the scientists who do.
• Effective communicator who can translate complex scientific and operational status into clear updates for leadership.

Bonus Points For

• Direct experience with automated, high‑throughput, or closed‑loop discovery environments (e.g., self‑driving labs, robotic synthesis and screening platforms), you've seen what it takes to make these systems produce real drug discovery output, not just proof‑of‑concept demos.
• Experience applying computational chemistry or cheminformatics in a hands‑on capacity, not just consuming model outputs, but contributing to how molecular design hypotheses are generated, scored, and prioritized.
• Experience building or scaling a discovery operation from early stage, standing up assay cascades, workflows, team structures, and vendor relationships without inheriting a mature infrastructure.
• Background across multiple therapeutic areas, giving you breadth in target biology and the flexibility to work across a diverse portfolio.
• Process‑oriented thinking: you instinctively look for ways to measure, standardize, and improve how work gets done, without letting process become bureaucracy.

Compensation

We offer competitive base compensation with bonus potential and generous early‑stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full‑time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer‑paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full‑time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range: $202,400 — $323,400 USD

About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard‑coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above,

We’re All In

Lila Sciences iscommitted to equal employment opportunityregardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.